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Data Monetisation and Data Valuation Training Course

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  1. Data Valuation Downloads
  2. Why we need to put a dollar value on data

    Data valuation 101: why you need hard numbers to succeed
    4 Topics
  3. Setting the scene - a Finance 101
    What are some financial metrics your management will care about?
    3 Topics
  4. The four categories of data value
    4 Topics
  5. Establishing a baseline
    The value of intangible assets
  6. Data valuation 102: how much is your data worth today?
    4 Topics
    |
    1 Quiz
  7. Fail-Proof Data Valuation Techniques
    An introduction to data valuation models
  8. Enhance Experience - how data can win you more business
    2 Topics
    |
    1 Quiz
  9. Wheelspin Wipeout - Put a price on waste and rework
    2 Topics
    |
    1 Quiz
  10. Eliminate ambiguity - how to drive productivity across your enterprise
    3 Topics
    |
    1 Quiz
  11. Opportunity knocks - where can we sell or barter our data?
    4 Topics
  12. Data Debt - the high cost of doing nothing
    2 Topics
    |
    1 Quiz
  13. Infonomics - a practical review
    7 Topics
    |
    1 Quiz
  14. How much does it cost to be wrong?
    1 Quiz
  15. Using data valuations
    How do we use these data valuations?
  16. Mapping data valuations to Enterprise value
  17. Running Data Monetisation Workshops
  18. Growing data value through time - Bill Schmarzo's Economic Value of Data
  19. Next steps
    1 Quiz
Lesson Progress
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Cutting costs with data

Waste and inefficiency are rife in most large enterprises, and it’s something that we’ve got to grapple with and we’ve got to drag down if we want to drive up our EBITDA figures and increase our enterprise value. Here are 4 ways you can choose from.

Reduce time wasted looking

Reduce the time your data science team take to find the right data. That will reduce the cost to produce your analytical insights.

Avoid unnecessary confusion costs

You can also take a look across the business at where data is being used today and the costs it’s creating. For example, are there teams that receive data from other parts of the business but after waste time cleaning and organising it so that they can put it to use in their own part of the business? The finance team is an exact example of this, where they have to spend hours putting together data from all parts of the business in order to produce the books and records on time.

Make more accurate decisions

So look at the decisions being made by the business and where they increase costs. How about you reduce undeliverable orders by improving location data? What about saving on posting and shipping? By improving data on the shipping requirements for each product and customer agreements? So if you’ve got seven days to ship a product, don’t expedite it and waste the money on overnight deliveries.

Share data for a discount

Are you able to share data with your suppliers that are valuable to them? Because if you can, you might be able to share that data in exchange for a discount on your purchase prices.

Stop struggling, start succeeding

learn how to get your data program funding

Quickly learn how to succeed with 3-5 minute long video lessons packed with practical advice you can use in your job today

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